Overview

Dataset statistics

Number of variables16
Number of observations578320
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory70.6 MiB
Average record size in memory128.0 B

Variable types

Text5
Categorical4
Numeric5
DateTime2

Alerts

event_id is highly overall correlated with line_item_idHigh correlation
id is highly overall correlated with item_id and 1 other fieldsHigh correlation
item_id is highly overall correlated with id and 1 other fieldsHigh correlation
line_item_id is highly overall correlated with event_idHigh correlation
name is highly overall correlated with id and 1 other fieldsHigh correlation

Reproduction

Analysis started2024-04-25 17:47:58.613712
Analysis finished2024-04-25 17:49:01.980359
Duration1 minute and 3.37 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

Distinct4594
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:02.284995image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters20819520
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowcda7bec0-7cbf-4145-baf9-e049bab94504
2nd rowcda7bec0-7cbf-4145-baf9-e049bab94504
3rd rowcda7bec0-7cbf-4145-baf9-e049bab94504
4th rowcda7bec0-7cbf-4145-baf9-e049bab94504
5th rowcda7bec0-7cbf-4145-baf9-e049bab94504
ValueCountFrequency (%)
eb7dcb88-073d-403e-bdd4-1e5725fe2338 372
 
0.1%
ebcb2343-be1b-421e-83eb-6f79a321d999 360
 
0.1%
be8ce4e3-c596-43c2-8b70-bdcecada2139 360
 
0.1%
e4431b51-8db8-4b4a-a871-d12e3eaca47d 360
 
0.1%
a7d9058a-163e-4632-9bde-1f57130130cb 360
 
0.1%
c391f179-9eb3-418d-9d7b-b261f2dc57a6 360
 
0.1%
12e94262-2eaa-47d9-85c9-6f55e434f5c8 360
 
0.1%
ebcea232-0615-44be-8f9e-338100c6b31c 360
 
0.1%
9ff854ce-3c64-4519-8bc8-4f33713a1457 348
 
0.1%
82e02b41-5f63-429f-8e92-1787d86a0b66 348
 
0.1%
Other values (4584) 574732
99.4%
2024-04-25T17:49:02.967919image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2313280
 
11.1%
4 1671580
 
8.0%
9 1235266
 
5.9%
a 1232212
 
5.9%
b 1220087
 
5.9%
8 1209352
 
5.8%
2 1118661
 
5.4%
f 1095820
 
5.3%
d 1093437
 
5.3%
3 1090921
 
5.2%
Other values (7) 7538904
36.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20819520
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 2313280
 
11.1%
4 1671580
 
8.0%
9 1235266
 
5.9%
a 1232212
 
5.9%
b 1220087
 
5.9%
8 1209352
 
5.8%
2 1118661
 
5.4%
f 1095820
 
5.3%
d 1093437
 
5.3%
3 1090921
 
5.2%
Other values (7) 7538904
36.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20819520
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 2313280
 
11.1%
4 1671580
 
8.0%
9 1235266
 
5.9%
a 1232212
 
5.9%
b 1220087
 
5.9%
8 1209352
 
5.8%
2 1118661
 
5.4%
f 1095820
 
5.3%
d 1093437
 
5.3%
3 1090921
 
5.2%
Other values (7) 7538904
36.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20819520
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 2313280
 
11.1%
4 1671580
 
8.0%
9 1235266
 
5.9%
a 1232212
 
5.9%
b 1220087
 
5.9%
8 1209352
 
5.8%
2 1118661
 
5.4%
f 1095820
 
5.3%
d 1093437
 
5.3%
3 1090921
 
5.2%
Other values (7) 7538904
36.2%
Distinct4594
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:03.419656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters20819520
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row33b485de-7338-4997-b1d0-b988ba17b245
2nd row33b485de-7338-4997-b1d0-b988ba17b245
3rd row33b485de-7338-4997-b1d0-b988ba17b245
4th row33b485de-7338-4997-b1d0-b988ba17b245
5th row33b485de-7338-4997-b1d0-b988ba17b245
ValueCountFrequency (%)
5d53495a-55ac-49bf-b876-ad1ac4b8d2a4 372
 
0.1%
aa3a57b3-6636-4b91-8fa8-56b0524de6c2 360
 
0.1%
9d0efad8-bdd4-4b17-a139-adb4cd402d76 360
 
0.1%
c13e0d64-9d9d-434a-8066-896aca2b2530 360
 
0.1%
2ec6536e-862c-4dcf-af43-cef24a22eb64 360
 
0.1%
27fe2b8f-2aa8-4dae-ac1a-adf9b2c138ea 360
 
0.1%
2a61928a-211f-4825-b964-b00d021b9ba6 360
 
0.1%
a059f5f7-bda6-4ffa-a6e5-111f5fdbc23e 360
 
0.1%
258d1ad8-930a-44f4-b5d9-274b0cc0d44e 348
 
0.1%
8dc91d12-bcdb-4ab5-9ad9-6995d7d6bb4c 348
 
0.1%
Other values (4584) 574732
99.4%
2024-04-25T17:49:04.124181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2313280
 
11.1%
4 1665963
 
8.0%
9 1249804
 
6.0%
8 1218728
 
5.9%
b 1210117
 
5.8%
a 1209862
 
5.8%
6 1108686
 
5.3%
2 1106636
 
5.3%
5 1093922
 
5.3%
3 1093060
 
5.3%
Other values (7) 7549462
36.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20819520
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 2313280
 
11.1%
4 1665963
 
8.0%
9 1249804
 
6.0%
8 1218728
 
5.9%
b 1210117
 
5.8%
a 1209862
 
5.8%
6 1108686
 
5.3%
2 1106636
 
5.3%
5 1093922
 
5.3%
3 1093060
 
5.3%
Other values (7) 7549462
36.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20819520
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 2313280
 
11.1%
4 1665963
 
8.0%
9 1249804
 
6.0%
8 1218728
 
5.9%
b 1210117
 
5.8%
a 1209862
 
5.8%
6 1108686
 
5.3%
2 1106636
 
5.3%
5 1093922
 
5.3%
3 1093060
 
5.3%
Other values (7) 7549462
36.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20819520
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 2313280
 
11.1%
4 1665963
 
8.0%
9 1249804
 
6.0%
8 1218728
 
5.9%
b 1210117
 
5.8%
a 1209862
 
5.8%
6 1108686
 
5.3%
2 1106636
 
5.3%
5 1093922
 
5.3%
3 1093060
 
5.3%
Other values (7) 7549462
36.3%
Distinct243
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:04.649969image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length51
Median length33
Mean length10.498835
Min length4

Characters and Unicode

Total characters6071686
Distinct characters59
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSaint Helena
2nd rowSaint Helena
3rd rowSaint Helena
4th rowSaint Helena
5th rowSaint Helena
ValueCountFrequency (%)
islands 34926
 
4.0%
and 23647
 
2.7%
saint 16041
 
1.8%
republic 13822
 
1.6%
united 11561
 
1.3%
island 10742
 
1.2%
french 8967
 
1.0%
states 7904
 
0.9%
new 7840
 
0.9%
territory 7344
 
0.8%
Other values (298) 735265
83.7%
2024-04-25T17:49:05.668436image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 828112
 
13.6%
n 497581
 
8.2%
i 487672
 
8.0%
e 442152
 
7.3%
r 363961
 
6.0%
299739
 
4.9%
o 297865
 
4.9%
t 256241
 
4.2%
l 251629
 
4.1%
s 242291
 
4.0%
Other values (49) 2104443
34.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6071686
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 828112
 
13.6%
n 497581
 
8.2%
i 487672
 
8.0%
e 442152
 
7.3%
r 363961
 
6.0%
299739
 
4.9%
o 297865
 
4.9%
t 256241
 
4.2%
l 251629
 
4.1%
s 242291
 
4.0%
Other values (49) 2104443
34.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6071686
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 828112
 
13.6%
n 497581
 
8.2%
i 487672
 
8.0%
e 442152
 
7.3%
r 363961
 
6.0%
299739
 
4.9%
o 297865
 
4.9%
t 256241
 
4.2%
l 251629
 
4.1%
s 242291
 
4.0%
Other values (49) 2104443
34.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6071686
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 828112
 
13.6%
n 497581
 
8.2%
i 487672
 
8.0%
e 442152
 
7.3%
r 363961
 
6.0%
299739
 
4.9%
o 297865
 
4.9%
t 256241
 
4.2%
l 251629
 
4.1%
s 242291
 
4.0%
Other values (49) 2104443
34.7%

currency
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
USD
198037 
GBP
191403 
NGN
188880 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1734960
Distinct characters7
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNGN
2nd rowNGN
3rd rowNGN
4th rowNGN
5th rowNGN

Common Values

ValueCountFrequency (%)
USD 198037
34.2%
GBP 191403
33.1%
NGN 188880
32.7%

Length

2024-04-25T17:49:06.030935image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-25T17:49:06.466944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
usd 198037
34.2%
gbp 191403
33.1%
ngn 188880
32.7%

Most occurring characters

ValueCountFrequency (%)
G 380283
21.9%
N 377760
21.8%
U 198037
11.4%
S 198037
11.4%
D 198037
11.4%
B 191403
11.0%
P 191403
11.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1734960
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 380283
21.9%
N 377760
21.8%
U 198037
11.4%
S 198037
11.4%
D 198037
11.4%
B 191403
11.0%
P 191403
11.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1734960
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 380283
21.9%
N 377760
21.8%
U 198037
11.4%
S 198037
11.4%
D 198037
11.4%
B 191403
11.0%
P 191403
11.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1734960
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 380283
21.9%
N 377760
21.8%
U 198037
11.4%
S 198037
11.4%
D 198037
11.4%
B 191403
11.0%
P 191403
11.0%

event_id
Real number (ℝ)

HIGH CORRELATION 

Distinct72570
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean88235.38
Minimum14786
Maximum161960
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:06.854642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum14786
5-th percentile21966
Q151318
median88373
Q3125003
95-th percentile155050.05
Maximum161960
Range147174
Interquartile range (IQR)73685

Descriptive statistics

Standard deviation42541.875
Coefficient of variation (CV)0.48214078
Kurtosis-1.1973425
Mean88235.38
Median Absolute Deviation (MAD)36812
Skewness0.0055772593
Sum5.1028285 × 1010
Variance1.8098111 × 109
MonotonicityNot monotonic
2024-04-25T17:49:07.747192image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39608 12
 
< 0.1%
39642 12
 
< 0.1%
39635 12
 
< 0.1%
39636 12
 
< 0.1%
39637 12
 
< 0.1%
39638 12
 
< 0.1%
39639 12
 
< 0.1%
39640 12
 
< 0.1%
39641 12
 
< 0.1%
39643 12
 
< 0.1%
Other values (72560) 578200
> 99.9%
ValueCountFrequency (%)
14786 6
< 0.1%
14787 6
< 0.1%
14788 6
< 0.1%
14789 6
< 0.1%
14790 6
< 0.1%
14791 6
< 0.1%
14792 6
< 0.1%
14793 6
< 0.1%
14794 6
< 0.1%
14795 6
< 0.1%
ValueCountFrequency (%)
161960 2
< 0.1%
161959 2
< 0.1%
161958 2
< 0.1%
161957 2
< 0.1%
161956 2
< 0.1%
161955 2
< 0.1%
161954 2
< 0.1%
161953 2
< 0.1%
161952 2
< 0.1%
161951 2
< 0.1%
Distinct71881
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:08.895546image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length144
Median length142
Mean length92.565272
Min length66

Characters and Unicode

Total characters53532348
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1425 ?
Unique (%)0.2%

Sample

1st row{"timestamp": "2024-03-26T22:05:58.863661", "event_type": "visit"}
2nd row{"timestamp": "2024-03-27T07:14:33.987347", "event_type": "visit"}
3rd row{"timestamp": "2024-03-30T04:03:10.406559", "event_type": "visit"}
4th row{"timestamp": "2024-03-30T04:03:10.406561", "event_type": "visit"}
5th row{"item_id": 4, "quantity": 2, "timestamp": "2024-03-30T04:03:10.406769", "event_type": "add_to_cart"}
ValueCountFrequency (%)
timestamp 578320
15.3%
event_type 578320
15.3%
item_id 403425
 
10.7%
quantity 269335
 
7.1%
add_to_cart 269335
 
7.1%
visit 143154
 
3.8%
remove_from_cart 134090
 
3.5%
4 81865
 
2.2%
3 81057
 
2.1%
5 80659
 
2.1%
Other values (74899) 1166204
30.8%
2024-04-25T17:49:10.140701image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 6226008
 
11.6%
t 4166512
 
7.8%
0 3269029
 
6.1%
3207444
 
6.0%
e 3148507
 
5.9%
: 3049522
 
5.7%
3 2221863
 
4.2%
i 1983202
 
3.7%
2 1842341
 
3.4%
m 1828245
 
3.4%
Other values (31) 22589675
42.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 53532348
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
" 6226008
 
11.6%
t 4166512
 
7.8%
0 3269029
 
6.1%
3207444
 
6.0%
e 3148507
 
5.9%
: 3049522
 
5.7%
3 2221863
 
4.2%
i 1983202
 
3.7%
2 1842341
 
3.4%
m 1828245
 
3.4%
Other values (31) 22589675
42.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 53532348
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
" 6226008
 
11.6%
t 4166512
 
7.8%
0 3269029
 
6.1%
3207444
 
6.0%
e 3148507
 
5.9%
: 3049522
 
5.7%
3 2221863
 
4.2%
i 1983202
 
3.7%
2 1842341
 
3.4%
m 1828245
 
3.4%
Other values (31) 22589675
42.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 53532348
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
" 6226008
 
11.6%
t 4166512
 
7.8%
0 3269029
 
6.1%
3207444
 
6.0%
e 3148507
 
5.9%
: 3049522
 
5.7%
3 2221863
 
4.2%
i 1983202
 
3.7%
2 1842341
 
3.4%
m 1828245
 
3.4%
Other values (31) 22589675
42.2%
Distinct70287
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
Minimum2024-03-19 04:06:12.469246
Maximum2024-03-30 04:20:18.189028
2024-04-25T17:49:10.528315image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:49:11.202279image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
Distinct4594
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:11.610884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Length

Max length36
Median length36
Mean length36
Min length36

Characters and Unicode

Total characters20819520
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row9e950ce3-2e12-479c-a051-493c1a497d49
2nd row9e950ce3-2e12-479c-a051-493c1a497d49
3rd row9e950ce3-2e12-479c-a051-493c1a497d49
4th row9e950ce3-2e12-479c-a051-493c1a497d49
5th row9e950ce3-2e12-479c-a051-493c1a497d49
ValueCountFrequency (%)
5cc9c814-c69a-4831-9b50-92abe2c1dea2 372
 
0.1%
5984596b-0ed5-4571-8e79-b261e6f138ad 360
 
0.1%
4a57c86d-c1e1-43fb-aef4-374b09d88047 360
 
0.1%
4575a5fe-bc4b-4745-885c-c22a27fd2f38 360
 
0.1%
9af259a9-1642-4f2c-bc78-1161bc747e98 360
 
0.1%
26848185-83a6-46a5-9e40-3d49c9d64ef1 360
 
0.1%
3ba26ffc-3230-4dab-bb58-b9a752cf8d76 360
 
0.1%
da2afd0d-73e4-41c5-bade-b4f1ef1581d1 360
 
0.1%
c592a392-d605-4b0c-af69-ee6ea582a09f 348
 
0.1%
8959ec9c-9e20-4b54-ad6e-c545423bd105 348
 
0.1%
Other values (4584) 574732
99.4%
2024-04-25T17:49:12.300811image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 2313280
 
11.1%
4 1655187
 
8.0%
8 1241954
 
6.0%
9 1236115
 
5.9%
a 1214744
 
5.8%
b 1213617
 
5.8%
d 1125144
 
5.4%
6 1111716
 
5.3%
c 1111102
 
5.3%
7 1098519
 
5.3%
Other values (7) 7498142
36.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 20819520
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 2313280
 
11.1%
4 1655187
 
8.0%
8 1241954
 
6.0%
9 1236115
 
5.9%
a 1214744
 
5.8%
b 1213617
 
5.8%
d 1125144
 
5.4%
6 1111716
 
5.3%
c 1111102
 
5.3%
7 1098519
 
5.3%
Other values (7) 7498142
36.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 20819520
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 2313280
 
11.1%
4 1655187
 
8.0%
8 1241954
 
6.0%
9 1236115
 
5.9%
a 1214744
 
5.8%
b 1213617
 
5.8%
d 1125144
 
5.4%
6 1111716
 
5.3%
c 1111102
 
5.3%
7 1098519
 
5.3%
Other values (7) 7498142
36.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 20819520
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 2313280
 
11.1%
4 1655187
 
8.0%
8 1241954
 
6.0%
9 1236115
 
5.9%
a 1214744
 
5.8%
b 1213617
 
5.8%
d 1125144
 
5.4%
6 1111716
 
5.3%
c 1111102
 
5.3%
7 1098519
 
5.3%
Other values (7) 7498142
36.0%

status
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
failed
196383 
success
192594 
cancelled
189343 

Length

Max length9
Median length7
Mean length7.3152286
Min length6

Characters and Unicode

Total characters4230543
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowsuccess
2nd rowsuccess
3rd rowsuccess
4th rowsuccess
5th rowsuccess

Common Values

ValueCountFrequency (%)
failed 196383
34.0%
success 192594
33.3%
cancelled 189343
32.7%

Length

2024-04-25T17:49:12.605449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-25T17:49:12.847307image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
failed 196383
34.0%
success 192594
33.3%
cancelled 189343
32.7%

Most occurring characters

ValueCountFrequency (%)
e 767663
18.1%
c 763874
18.1%
s 577782
13.7%
l 575069
13.6%
a 385726
9.1%
d 385726
9.1%
f 196383
 
4.6%
i 196383
 
4.6%
u 192594
 
4.6%
n 189343
 
4.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4230543
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 767663
18.1%
c 763874
18.1%
s 577782
13.7%
l 575069
13.6%
a 385726
9.1%
d 385726
9.1%
f 196383
 
4.6%
i 196383
 
4.6%
u 192594
 
4.6%
n 189343
 
4.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4230543
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 767663
18.1%
c 763874
18.1%
s 577782
13.7%
l 575069
13.6%
a 385726
9.1%
d 385726
9.1%
f 196383
 
4.6%
i 196383
 
4.6%
u 192594
 
4.6%
n 189343
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4230543
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 767663
18.1%
c 763874
18.1%
s 577782
13.7%
l 575069
13.6%
a 385726
9.1%
d 385726
9.1%
f 196383
 
4.6%
i 196383
 
4.6%
u 192594
 
4.6%
n 189343
 
4.5%
Distinct4594
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
Minimum2024-03-30 04:06:10.418189
Maximum2024-03-30 04:20:18.189028
2024-04-25T17:49:13.105388image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:49:13.378088image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

line_item_id
Real number (ℝ)

HIGH CORRELATION 

Distinct31741
Distinct (%)5.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19034.445
Minimum3201
Maximum34941
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:13.645418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum3201
5-th percentile4776
Q111108
median19067
Q326960
95-th percentile33354.05
Maximum34941
Range31740
Interquartile range (IQR)15852

Descriptive statistics

Standard deviation9153.5417
Coefficient of variation (CV)0.48089355
Kurtosis-1.1983303
Mean19034.445
Median Absolute Deviation (MAD)7930
Skewness0.0051960703
Sum1.1008 × 1010
Variance83787325
MonotonicityNot monotonic
2024-04-25T17:49:13.938030image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12802 31
 
< 0.1%
12800 31
 
< 0.1%
12805 31
 
< 0.1%
12803 31
 
< 0.1%
12811 31
 
< 0.1%
12810 31
 
< 0.1%
12801 31
 
< 0.1%
12806 31
 
< 0.1%
12804 31
 
< 0.1%
12808 31
 
< 0.1%
Other values (31731) 578010
99.9%
ValueCountFrequency (%)
3201 14
< 0.1%
3202 14
< 0.1%
3203 14
< 0.1%
3204 14
< 0.1%
3205 14
< 0.1%
3206 14
< 0.1%
3207 4
 
< 0.1%
3208 18
< 0.1%
3209 18
< 0.1%
3210 18
< 0.1%
ValueCountFrequency (%)
34941 10
 
< 0.1%
34940 10
 
< 0.1%
34939 15
< 0.1%
34938 15
< 0.1%
34937 15
< 0.1%
34936 15
< 0.1%
34935 15
< 0.1%
34934 25
< 0.1%
34933 25
< 0.1%
34932 25
< 0.1%

item_id
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.9957411
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:14.212702image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q312
95-th percentile15
Maximum15
Range14
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.3229022
Coefficient of variation (CV)0.54065059
Kurtosis-1.2086029
Mean7.9957411
Median Absolute Deviation (MAD)4
Skewness0.0015367804
Sum4624097
Variance18.687483
MonotonicityNot monotonic
2024-04-25T17:49:14.419408image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
11 39715
 
6.9%
15 39268
 
6.8%
8 39162
 
6.8%
10 39084
 
6.8%
2 38997
 
6.7%
1 38866
 
6.7%
4 38842
 
6.7%
6 38835
 
6.7%
5 38782
 
6.7%
12 38440
 
6.6%
Other values (5) 188329
32.6%
ValueCountFrequency (%)
1 38866
6.7%
2 38997
6.7%
3 37501
6.5%
4 38842
6.7%
5 38782
6.7%
6 38835
6.7%
7 38291
6.6%
8 39162
6.8%
9 36979
6.4%
10 39084
6.8%
ValueCountFrequency (%)
15 39268
6.8%
14 38043
6.6%
13 37515
6.5%
12 38440
6.6%
11 39715
6.9%
10 39084
6.8%
9 36979
6.4%
8 39162
6.8%
7 38291
6.6%
6 38835
6.7%

quantity
Categorical

Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
3
118399 
4
117370 
5
114793 
2
114263 
1
113495 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters578320
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
3 118399
20.5%
4 117370
20.3%
5 114793
19.8%
2 114263
19.8%
1 113495
19.6%

Length

2024-04-25T17:49:14.654901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-25T17:49:14.915283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
3 118399
20.5%
4 117370
20.3%
5 114793
19.8%
2 114263
19.8%
1 113495
19.6%

Most occurring characters

ValueCountFrequency (%)
3 118399
20.5%
4 117370
20.3%
5 114793
19.8%
2 114263
19.8%
1 113495
19.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 578320
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
3 118399
20.5%
4 117370
20.3%
5 114793
19.8%
2 114263
19.8%
1 113495
19.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 578320
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
3 118399
20.5%
4 117370
20.3%
5 114793
19.8%
2 114263
19.8%
1 113495
19.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 578320
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
3 118399
20.5%
4 117370
20.3%
5 114793
19.8%
2 114263
19.8%
1 113495
19.6%

id
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.9957411
Minimum1
Maximum15
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:15.150977image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median8
Q312
95-th percentile15
Maximum15
Range14
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.3229022
Coefficient of variation (CV)0.54065059
Kurtosis-1.2086029
Mean7.9957411
Median Absolute Deviation (MAD)4
Skewness0.0015367804
Sum4624097
Variance18.687483
MonotonicityNot monotonic
2024-04-25T17:49:15.375520image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
11 39715
 
6.9%
15 39268
 
6.8%
8 39162
 
6.8%
10 39084
 
6.8%
2 38997
 
6.7%
1 38866
 
6.7%
4 38842
 
6.7%
6 38835
 
6.7%
5 38782
 
6.7%
12 38440
 
6.6%
Other values (5) 188329
32.6%
ValueCountFrequency (%)
1 38866
6.7%
2 38997
6.7%
3 37501
6.5%
4 38842
6.7%
5 38782
6.7%
6 38835
6.7%
7 38291
6.6%
8 39162
6.8%
9 36979
6.4%
10 39084
6.8%
ValueCountFrequency (%)
15 39268
6.8%
14 38043
6.6%
13 37515
6.5%
12 38440
6.6%
11 39715
6.9%
10 39084
6.8%
9 36979
6.4%
8 39162
6.8%
7 38291
6.6%
6 38835
6.7%

name
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size4.4 MiB
Canon EOS R5 Camera
39715 
Fitbit Charge 4
39268 
Sony WH-1000XM4 Headphones
39162 
Dell XPS 13 Laptop
39084 
Samsung Galaxy S21
38997 
Other values (10)
382094 

Length

Max length27
Median length23
Mean length18.463416
Min length9

Characters and Unicode

Total characters10677763
Distinct characters53
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMicrosoft Xbox Series X
2nd rowMicrosoft Xbox Series X
3rd rowMicrosoft Xbox Series X
4th rowMicrosoft Xbox Series X
5th rowMicrosoft Xbox Series X

Common Values

ValueCountFrequency (%)
Canon EOS R5 Camera 39715
 
6.9%
Fitbit Charge 4 39268
 
6.8%
Sony WH-1000XM4 Headphones 39162
 
6.8%
Dell XPS 13 Laptop 39084
 
6.8%
Samsung Galaxy S21 38997
 
6.7%
iPhone 13 38866
 
6.7%
Microsoft Xbox Series X 38842
 
6.7%
Adidas Ultraboost 38835
 
6.7%
Nike Air Max 270 38782
 
6.7%
Coca-Cola 12-Pack 38440
 
6.6%
Other values (5) 188329
32.6%

Length

2024-04-25T17:49:15.636510image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
13 77950
 
4.3%
samsung 77040
 
4.2%
sony 76663
 
4.2%
canon 39715
 
2.2%
eos 39715
 
2.2%
r5 39715
 
2.2%
camera 39715
 
2.2%
4 39268
 
2.2%
charge 39268
 
2.2%
fitbit 39268
 
2.2%
Other values (34) 1306032
72.0%

Most occurring characters

ValueCountFrequency (%)
1236029
 
11.6%
a 811540
 
7.6%
o 693143
 
6.5%
e 539538
 
5.1%
n 498178
 
4.7%
i 461235
 
4.3%
S 460379
 
4.3%
t 458650
 
4.3%
r 386424
 
3.6%
s 384877
 
3.6%
Other values (43) 4747770
44.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10677763
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1236029
 
11.6%
a 811540
 
7.6%
o 693143
 
6.5%
e 539538
 
5.1%
n 498178
 
4.7%
i 461235
 
4.3%
S 460379
 
4.3%
t 458650
 
4.3%
r 386424
 
3.6%
s 384877
 
3.6%
Other values (43) 4747770
44.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10677763
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1236029
 
11.6%
a 811540
 
7.6%
o 693143
 
6.5%
e 539538
 
5.1%
n 498178
 
4.7%
i 461235
 
4.3%
S 460379
 
4.3%
t 458650
 
4.3%
r 386424
 
3.6%
s 384877
 
3.6%
Other values (43) 4747770
44.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10677763
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1236029
 
11.6%
a 811540
 
7.6%
o 693143
 
6.5%
e 539538
 
5.1%
n 498178
 
4.7%
i 461235
 
4.3%
S 460379
 
4.3%
t 458650
 
4.3%
r 386424
 
3.6%
s 384877
 
3.6%
Other values (43) 4747770
44.5%

price
Real number (ℝ)

Distinct14
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean707.44861
Minimum5.99
Maximum3999.99
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.4 MiB
2024-04-25T17:49:15.876373image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum5.99
5-th percentile5.99
Q1149.95
median349.99
Q3899.99
95-th percentile3999.99
Maximum3999.99
Range3994
Interquartile range (IQR)750.04

Descriptive statistics

Standard deviation972.91532
Coefficient of variation (CV)1.3752452
Kurtosis6.0818789
Mean707.44861
Median Absolute Deviation (MAD)220
Skewness2.5797312
Sum4.0913168 × 108
Variance946564.22
MonotonicityNot monotonic
2024-04-25T17:49:16.101760image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
499.99 76343
13.2%
3999.99 39715
 
6.9%
149.95 39268
 
6.8%
349.99 39162
 
6.8%
1299.99 39084
 
6.8%
899.99 38997
 
6.7%
1099.99 38866
 
6.7%
180 38835
 
6.7%
129.99 38782
 
6.7%
5.99 38440
 
6.6%
Other values (4) 150828
26.1%
ValueCountFrequency (%)
5.99 38440
6.6%
12.99 37515
6.5%
129.99 38782
6.7%
149.95 39268
6.8%
180 38835
6.7%
249.99 38291
6.6%
299.99 36979
6.4%
349.99 39162
6.8%
499.99 76343
13.2%
799.99 38043
6.6%
ValueCountFrequency (%)
3999.99 39715
6.9%
1299.99 39084
6.8%
1099.99 38866
6.7%
899.99 38997
6.7%
799.99 38043
6.6%
499.99 76343
13.2%
349.99 39162
6.8%
299.99 36979
6.4%
249.99 38291
6.6%
180 38835
6.7%

Interactions

2024-04-25T17:48:56.682826image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:49.149944image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:50.690287image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:52.848797image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:55.014617image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:56.996757image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:49.464687image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:51.113690image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:53.304891image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:55.327693image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:57.310901image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:49.762898image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:51.524424image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:53.744538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:55.788653image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:57.634337image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:50.081709image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:51.953645image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:54.124594image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:56.087231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:57.950691image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:50.378039image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:52.400285image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:54.575372image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2024-04-25T17:48:56.385597image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2024-04-25T17:49:16.343993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
currencyevent_ididitem_idline_item_idnamepricequantitystatus
currency1.000-0.0260.0020.002-0.0260.011-0.0060.0130.029
event_id-0.0261.0000.0010.0011.0000.0130.0040.0180.054
id0.0020.0011.0001.0000.0011.000-0.3020.0170.008
item_id0.0020.0011.0001.0000.0011.000-0.3020.0170.008
line_item_id-0.0261.0000.0010.0011.0000.0130.0040.0180.056
name0.0110.0131.0001.0000.0131.0000.1270.0210.010
price-0.0060.004-0.302-0.3020.0040.1271.0000.0110.003
quantity0.0130.0180.0170.0170.0180.0210.0111.0000.009
status0.0290.0540.0080.0080.0560.0100.0030.0091.000

Missing values

2024-04-25T17:48:58.632231image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-25T17:48:59.936160image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

customer_iddevice_idlocationcurrencyevent_idevent_dataevent_timestamporder_idstatuschecked_out_atline_item_iditem_idquantityidnameprice
0cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14786{"timestamp": "2024-03-26T22:05:58.863661", "event_type": "visit"}2024-03-26 22:05:58.8636619e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
1cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14787{"timestamp": "2024-03-27T07:14:33.987347", "event_type": "visit"}2024-03-27 07:14:33.9873479e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
2cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14788{"timestamp": "2024-03-30T04:03:10.406559", "event_type": "visit"}2024-03-30 04:03:10.4065599e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
3cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14789{"timestamp": "2024-03-30T04:03:10.406561", "event_type": "visit"}2024-03-30 04:03:10.4065619e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
4cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14790{"item_id": 4, "quantity": 2, "timestamp": "2024-03-30T04:03:10.406769", "event_type": "add_to_cart"}2024-03-30 04:03:10.4067699e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
5cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14791{"item_id": 4, "timestamp": "2024-03-30T04:03:10.406774", "event_type": "remove_from_cart"}2024-03-30 04:03:10.4067749e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
6cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14792{"item_id": 5, "quantity": 4, "timestamp": "2024-03-30T04:03:10.406775", "event_type": "add_to_cart"}2024-03-30 04:03:10.4067759e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
7cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14793{"item_id": 5, "timestamp": "2024-03-30T04:03:10.406778", "event_type": "remove_from_cart"}2024-03-30 04:03:10.4067789e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
8cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14794{"item_id": 9, "quantity": 5, "timestamp": "2024-03-30T04:03:10.406779", "event_type": "add_to_cart"}2024-03-30 04:03:10.4067799e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
9cda7bec0-7cbf-4145-baf9-e049bab9450433b485de-7338-4997-b1d0-b988ba17b245Saint HelenaNGN14795{"item_id": 12, "quantity": 1, "timestamp": "2024-03-30T04:03:10.406782", "event_type": "add_to_cart"}2024-03-30 04:03:10.4067829e950ce3-2e12-479c-a051-493c1a497d49success2024-03-30 04:19:10.4067943201424Microsoft Xbox Series X499.99
customer_iddevice_idlocationcurrencyevent_idevent_dataevent_timestamporder_idstatuschecked_out_atline_item_iditem_idquantityidnameprice
5783103aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161941{"timestamp": "2024-03-30T04:03:18.223372", "event_type": "visit"}2024-03-30 04:03:18.2233724c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99
5783113aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161942{"timestamp": "2024-03-30T04:03:18.223372", "event_type": "visit"}2024-03-30 04:03:18.2233724c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99
5783123aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161943{"timestamp": "2024-03-30T04:03:18.223373", "event_type": "visit"}2024-03-30 04:03:18.2233734c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99
5783133aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161944{"item_id": 10, "quantity": 4, "timestamp": "2024-03-30T04:03:18.223416", "event_type": "add_to_cart"}2024-03-30 04:03:18.2234164c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99
5783143aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161945{"item_id": 10, "timestamp": "2024-03-30T04:03:18.223419", "event_type": "remove_from_cart"}2024-03-30 04:03:18.2234194c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99
5783153aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161946{"item_id": 6, "quantity": 3, "timestamp": "2024-03-30T04:03:18.223419", "event_type": "add_to_cart"}2024-03-30 04:03:18.2234194c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99
5783163aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161947{"item_id": 4, "quantity": 3, "timestamp": "2024-03-30T04:03:18.223421", "event_type": "add_to_cart"}2024-03-30 04:03:18.2234214c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99
5783173aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161948{"item_id": 13, "quantity": 2, "timestamp": "2024-03-30T04:03:18.223423", "event_type": "add_to_cart"}2024-03-30 04:03:18.2234234c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99
5783183aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161949{"item_id": 3, "quantity": 2, "timestamp": "2024-03-30T04:03:18.223424", "event_type": "add_to_cart"}2024-03-30 04:03:18.2234244c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99
5783193aa213f4-2699-43b4-96b8-bf0de1cda13335a035eb-5b04-45ff-8be7-66b8bbcc20a4LiechtensteinGBP161950{"status": "cancelled", "order_id": "4c2defc5-b1fe-4f2f-90b1-6ccce7bf481d", "timestamp": "2024-03-30T04:19:18.223427", "event_type": "checkout"}2024-03-30 04:19:18.2234274c2defc5-b1fe-4f2f-90b1-6ccce7bf481dcancelled2024-03-30 04:19:18.22342734939323Sony PlayStation 5499.99